🛒 AI is quietly becoming the new shopping layer

Shopping is now the third-most-used AI application, according to an Epsilon research report.

But there’s a huge gap in how people use it: 42% of surveyed shoppers use AI to compare prices, while only 16% let AI finalize a purchase.

That 26-point gap could be the biggest opportunity in agentic commerce.

The shift is already showing up in the numbers. Shopify says AI-driven traffic to merchants grew 8× year over year in Q1 2026, while orders from AI-powered searches rose nearly 13%. Buyers arriving through AI channels were also ordering at almost twice the rate of other channels.

Shopify is connecting Shop Pay to Meta’s Muse, giving outside AI agents a path into its commerce infrastructure.

Amazon is taking the opposite approach, blocking dozens of third-party shopping agents, including ChatGPT, while pushing shoppers toward its own AI assistant, Rufus.

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Opus 5.5 can disrupt the educational videos industry.

Electricity

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axios: Donald Trump plans a private White House dinner with Anthropic CEO Dario Amodei, their first one-on-one meeting.

Trump issued the invitation himself after Amodei missed last week's state dinner for Chinese President Xi Jinping

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🗣️Dario Amodei: If my revenue is not $1 trillion by 2027, Anthropic will go bankrupt.

“I could assume that revenue will continue growing 10x a year.”

“$100 billion at the end of 2026 and $1 trillion at the end of 2027.”

“I could buy a trillion dollars a year of compute.”

“But if my revenue is not a trillion dollars, if it’s even $800 billion, there’s no hedge on earth that could stop me from going bankrupt.”

“If the growth rate is 5x instead of 10x, then you go bankrupt.”

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❗️The biotech rabbit hole is getting strange

The wild part of AI in biology right now isn’t that models can predict proteins.It’s that the entire research loop is starting to close.

This week alone:

• Stanford ran a virtual biotech with 37,000 AI agents that generated and tested hypotheses at a scale humans couldn’t realistically match. One proposed cancer therapy was later independently confirmed by a pharmaceutical company seven months afterward.
• Novo Nordisk revealed it now has 600+ AI and digital employees and more than 30 AI partnerships embedded in its actual R&D operation.
• Nvidia-backed Iambic filed for a US IPO with an AI-designed oncology drug already in clinical development, alongside a new partnership with AbbVie.
• A model trained on 20,000+ private pharmaceutical protein structures reportedly outperformed public models, raising a potentially bigger question: is proprietary biological data becoming the real moat?
• Stanford trained a cell model on 112 million cells across 12 species, pushing toward something closer to a general-purpose model of biology.
• Anthropic is even operating a molecular-biology lab where humans and AI agents generate hypotheses and run physical experiments.

And that points to a strange new bottleneck. AI may soon be able to generate biological hypotheses faster than scientists can physically test them.

At that point, the limiting factor isn’t just intelligence. It’s data, lab capacity and the speed at which reality can catch up with the machines.

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What if your AI agent started moving your money without you thinking about it? 🤔

Apollo Global Management is warning about an “agentic bank run.”

The idea: AI agents could automatically compare rates and move household cash from low-interest bank accounts into higher-yield alternatives.

That sounds harmless until millions of agents do it at once.

Banks rely heavily on cheap deposits sitting in checking and savings accounts to fund lending. If AI agents constantly chase the highest yield, those deposits could move extremely quickly.

Humans might take days to switch banks.

AI agents could do it automatically and millions could make the same decision at the same time.

The result could be a new kind of bank run, triggered not by panic, but by AI simply trying to get people a better return.

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🙃 Elon Musk explains why, to an AI, talking to a human will be like talking to a tree

"Even in the most benign scenario where the AI is super friendly and wants to make you happy, our rate of communication is too slow."

"Our peak human bandwidth is only about 100 bits per second, roughly. Our input bandwidth is much higher because of vision, maybe a megabit or a few megabits per second from our eyes, which are effectively like cameras. But our output bandwidth is really low, maybe 100 bits per second, whereas computers are communicating at a trillion bits per second."

"So anything we can do to increase the communication speed of humans will improve the alignment of humans and machines. Because otherwise, to an AI that is communicating at a terabit a second, talking to a human will be like talking to a tree. You talk to a tree, it takes a long time to respond."

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🤖 Anthropic employees are reportedly preparing for the possibility that AI goes very wrong

Some early Anthropic employees are reportedly considering buying remote land in the U.S. as a fallback if AI development ever takes a catastrophic turn.

According to the WSJ, employees have also discussed doomsday scenarios and preparation plans in a private Slack, while Anthropic has its own space inside Berkeley’s AI-safety community.

The wider AI-safety scene has gone even further, with discussions around iodine pills, remote islands and electromagnetically shielded desert bunkers.

Anthropic employees reportedly even adopted a fitting motto:

“Things will never be chill again.”

One of the stranger details dates back to a 2022 gathering in the Bahamas attended by people from Anthropic and other AI labs. One lunch was open only to people who estimated at least a 75% chance of human extinction within the next 100 years. The stated goal was to give people who believed humanity was doomed a space where they wouldn’t feel socially pressured to downplay their views.

And Anthropic’s roots run deep in this mindset. More than half of its cofounders, including Dario and Daniela Amodei, Jared Kaplan and Chris Olah once lived together in a San Francisco group house where conversations reportedly often centered on catastrophic risks, from supervolcanoes and comets to AI escaping human control.

The people building some of the world’s most powerful AI systems are, apparently, also thinking about where to run if it all goes wrong.

Source.

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📊 The AI boom is starting to borrow from everyone

Big Tech is borrowing money like there’s no tomorrow to fund the AI race and it could make borrowing more expensive for the rest of us.

Investors have already poured around $500 billion into AI-related corporate debt this year. Amazon, Google, Meta, Microsoft and Oracle could collectively borrow more than $1 trillion over the next few years.

Tech giants have already pushed corporate borrowing to records in countries including the UK, Canada, Australia and Switzerland.

The problem is that there’s only so much capital to go around. If Big Tech keeps competing with governments and other companies for investors’ money, everyone may have to pay more to borrow.

That pressure is already showing up in U.S. bond markets, with the 10-year Treasury yield recently reaching its highest level since 2007.

And those rates don’t stay on Wall Street. They can eventually affect mortgages, car loans and credit cards.

Even retirement savings could be caught in the middle, since pension funds and insurers are major buyers of corporate debt.

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🤖 Anthropic launches Claude Sonnet 5.5

Anthropic has introduced Claude Sonnet 5.5, the second model in its Claude 5.5 family, positioned as a faster and cheaper alternative to Opus 5.5.

Sonnet 5.5 keeps the same price as Sonnet 5 but typically uses far fewer tokens, making it up to 30% cheaper per task in Anthropic’s testing. It also generates output more than 30% faster, making it the fastest Sonnet model yet.

The model improves across benchmarks, with Sonnet 5.5 at Low or Medium effort beating Sonnet 5’s best results on some tests while costing roughly a tenth as much.

Anthropic says it’s particularly suited for everyday coding and bug fixing, polished documents, slides, spreadsheets, UI design, and other well-scoped tasks where fast iteration matters.

Source.

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“Sir… Dario just dropped sonnet 5.5 and it moggs GPT-6 Sol on EVERYTHING at HALF the price of opus 5.5…”

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